Jun-Hee Yoon

Papers

Total Citations

H-Index

About

Jun-Hee Yoon is a robotics researcher whose work centers on precision visual sensing and calibration for automated assembly systems. His key contributions lie in developing methods to enhance measurement accuracy in complex, mirror-based vision systems—critical for tasks where robots must perceive and manipulate objects with high reliability. His most cited paper, "A Pyramidal Mirror System Calibration Method for Robotic Assembly" (2005, 7 citations), introduces a self-calibration technique that systematically reduces errors from multiple mirrors, improving system accuracy without external references. This work addresses a fundamental challenge in robotic vision: ensuring that what a robot "sees" aligns precisely with physical reality. Yoon’s approach to mirror position adjustment and calibration has practical implications for industrial automation, where even small errors can disrupt assembly processes. While his citation count is modest, his research represents a focused, technically rigorous contribution to the niche but essential field of visual sensor calibration. For students and researchers exploring sensor fusion or robotic perception, Yoon’s work offers a clear example of how systematic error correction can elevate the performance of vision-guided robotics.